Safety checklists have improved surgical outcomes; however, much of the literature comes from general surgery.
To identify the role of time-outs in neurosurgery, understand neurosurgeons' attitudes toward time-out, and highlight areas for improvement.
A cross-sectional study using a 15-item survey to evaluate how time-outs were performed across 5 hospitals affiliated with a single neurosurgery training program.
Surveys were sent to 51 neurosurgical faculty, fellows, and residents across 5 hospitals with a 72.5% response rate. At all hospitals, surgeons, anesthesiologists, registered nurses, and circulators were involved in time-outs. Although all required time-out before incision, there was no consensus regarding the precise timing of time-out, in policy or in practice. Overall, respondents believed the existing time-out was adequate for neurosurgical procedures (H1 17, 65.4%; H2 19, 86.4%; H3 14, 70.0%; H4 20, 80.0%; and H5 18, 78.3%). Of the respondents, 97.2% believed time-out made surgery safe, 94 by flexible World Health Organization guidelines, may reflect the origins of surgical time-outs in general surgery, rather than neurosurgery, underscoring the potential for time-out optimization with neurosurgery-specific considerations.Alternative transcription units (ATUs) are dynamically encoded under different conditions and display overlapping patterns (sharing one or more genes) under a specific condition in bacterial genomes. Genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques because of the complexity and dynamic nature of ATUs. Here, we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in Escherichia coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. In addition, the proportion of 5'- or 3'-end genes of the predicted ATUs, having documented transcription factor binding sites and transcription termination sites, was three times greater than that of no 5'- or 3'-end genes. We further evaluated the predicted ATUs by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. The results suggested that gene pairs frequently encoded in the same ATUs are more functionally related than those that can belong to two distinct ATUs. Overall, these results demonstrated the high reliability of predicted ATUs. We expect that the new insights derived by SeqATU will not only improve the understanding of the transcription mechanism of bacteria but also guide the reconstruction of a genome-scale transcriptional regulatory network.Sweetness is a sensation that contributes to the palatability of foods, which is the primary driver of food choice. https://www.selleckchem.com/products/glutathione.html Thus, understanding how to measure the appeal (hedonics) of sweetness and how to modify it are key to effecting dietary change for health. Sweet hedonics is multidimensional so can only be captured by multiple approaches including assessment of elements such as liking, preference, and consumption intent. There are both innate and learned components to the appeal of sweet foods and beverages. These are responsive to various behavioral and biological factors, suggesting the opportunity to modify intake. Given the high amount of added sugar intake in the United States and recommendations from many groups to reduce this, further exploration of current hypothesized approaches to moderate sugar intake (e.g., induced hedonic shift, use of low-calorie sweeteners) is warranted.Appropriate planning, execution, and reporting of statistical methods and results is critical for research transparency, validity, and reproducibility. This paper provides an overview of best practices for developing a statistical analysis plan a priori, conducting statistical analyses, and reporting statistical methods and results for human nutrition randomized controlled trials (RCTs). Readers are referred to the other NURISH (NUtrition inteRventIon reSearcH) publications for detailed information about the preparation and conduct of human nutrition RCTs. Collectively, the NURISH series outlines best practices for conducting human nutrition research.[This corrects the article doi 10.1590/1678-4685-GMB-2020-0083].To assess the effect of a consumer-based mobile meditation application (app) on wellness in outpatient obstetric and gynecology patients during the coronavirus disease 2019 (COVID-19) pandemic.
We conducted a randomized controlled trial at a university outpatient clinic of obstetric and gynecology patients during the COVID-19 pandemic. Women were randomly assigned to the intervention group, who was prescribed a mobile meditation app for 30 days, or the control group, which received standard care. The primary outcome was self-reported perceived stress. Secondary outcomes included self-reported depression, anxiety, sleep disturbance, and satisfaction with the meditation app. A sample size of 80 participants (40 per group) was calculated to achieve 84% power to detect a 3-point difference in the primary outcome.
From April to May 2020, 101 women were randomized in the study-50 in the meditation app group and 51 in the control group. Analysis was by intention-to-treat. Most characteristics were similar between groups. Perceived stress was significantly less in the intervention group at days 14 and 30 (mean difference 4.27, 95% CI 1.30-7.24, P=.005, d=0.69 and mean difference 4.28, 95% CI 1.68-6.88, P=.002, d=0.69, respectively). Self-reported depression and anxiety were significantly less in the intervention group at days 14 and 30 (depression P=.002 and P=.04; anxiety P=.01, and P=.04, respectively). Sleep disturbance was significantly less in the intervention group at days 14 and 30 (P=.001 and P=.02, respectively). More than 80% of those in the intervention group reported high satisfaction with the meditation app, and 93% reported that mindfulness meditation improved their stress.
Outpatient obstetric and gynecology patients who used the prescribed consumer-based mobile meditation app during the COVID-19 pandemic had significant reductions in perceived stress, depression, anxiety, and sleep disturbance compared with standard care.
ClinicalTrials.gov, NCT04329533.
ClinicalTrials.gov, NCT04329533.